Automatic classification of location contexts with decision trees

• Author(s): Santos, Maribel Yasmina ; Moreira, Adriano
• Date: 2006
• Persistent ID: http://hdl.handle.net/1822/5582
• Origin: RepositóriUM - Universidade do Minho
• Subject(s): Location contexts; Space models; Data mining; Decision trees; Clustering
• Document Type: Conference Object
• Language: English

Description

Location contexts are geographic regions, with well defined boundaries, that can be used to characterize the context of the persons lying inside them. In this paper we describe a process that exploits the increasing availability of geographic data to automatically create and classify location contexts. The pro-posed process generates new geographic regions from a database of Points Of Interest through the use of spatial clustering techniques, and classifies them automatically using a decision tree based method. Some preliminary results demonstrate the validity of this approach, while suggesting that a richer geographic database could produce location contexts of higher quality.